Arabic medical entity tagging using distant learning in a Multilingual Framework
نویسندگان
چکیده
http://dx.doi.org/10.1016/j.jksuci.2016.10.004 1319-1578/ 2016 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). ⇑ Corresponding author. E-mail addresses: [email protected] (V. Cotik), [email protected] (H. Rodríguez), [email protected] (J. Vivaldi). Peer review under responsibility of King Saud University.
منابع مشابه
Semantic Tagging of French Medical Entities Using Distant Learning
In this paper we present a semantic tagger aiming to detect relevant entities in French medical documents and tagging them with their appropriate semantic class. These experiments has been carried out in the framework of CLEF2015 eHealth contest that proposes a tagset of ten classes from UMLS taxonomy. The system presented uses a set of binary classifiers, and a combination mechanisms for combi...
متن کاملPragmatic Annotation of Discourse Markers in a Multilingual Parallel Corpus (Arabic- Spanish-English)
Discourse structure and coherence relations are one of the main inferential challenges addressed by computational pragmatics. The present study focuses on discourse markers as key elements in guiding the inferences of the statements in natural language. Through a rule-based approach for the automatic identification, classification and annotation of the discourse markers in a multilingual parall...
متن کاملIdentification of Languages in Algerian Arabic Multilingual Documents
This paper presents a language identification system designed to detect the language of each word, in its context, in a multilingual documents as generated in social media by bilingual/multilingual communities, in our case speakers of Algerian Arabic. We frame the task as a sequence tagging problem and use supervised machine learning with standard methods like HMM and Ngram classification taggi...
متن کاملروشی جدید جهت استخراج موجودیتهای اسمی در عربی کلاسیک
In Natural Language Processing (NLP) studies, developing resources and tools makes a contribution to extension and effectiveness of researches in each language. In recent years, Arabic Named Entity Recognition (ANER) has been considered by NLP researchers due to a significant impact on improving other NLP tasks such as Machine translation, Information retrieval, question answering, query result...
متن کاملNamed Entity Recognition in Persian Text using Deep Learning
Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...
متن کامل